LangWatch is an open-source platform designed for observing, evaluating, and optimizing Large Language Model (LLM) and agentic applications. It targets developers and teams building with LLMs, offering real-time tracing, performance analytics, and prompt management to enhance application quality and efficiency.

How It Works

LangWatch leverages OpenTelemetry for tracing, enabling real-time monitoring of LLM interactions. It supports both real-time and offline evaluations against datasets, allowing for performance comparisons across various components. The platform includes a "Datasets" feature for managing traced data and an "Optimization Studio" with a no-code interface and a DSL for prompt engineering and optimization, including auto-optimization via DSPy's MIPROv2. Human-in-the-loop annotations are integrated for data quality improvement.

Quick Start & Requirements

• Install: pip install langwatch
• Prerequisites: Docker for local setup. Environment variables LANGWATCH_API_KEY and LANGWATCH_ENDPOINT may be required for self-hosted instances.
• Setup: Local setup via Docker is described as under 30 seconds.
• Docs: https://docs.langwatch.ai/

Highlighted Details

• Framework and LLM agnostic, supporting integrations with LangGraph, DSPy, Langflow, Flowise, and numerous LLM providers (OpenAI, Azure, Bedrock, Gemini, etc.) via OpenTelemetry.
• Offers multiple deployment options: Cloud, self-hosted (OnPrem) with Azure AD support, and hybrid setups.
• Includes a JavaScript SDK and supports community standards like OpenInference and OpenLLMetry.
• Features an annotation interface for human-in-the-loop data labeling and model fine-tuning.

Maintenance & Community

• Active community with Discord and Twitter presence.
• Contributions are welcomed via GitHub.
• Enterprise support is available.

Licensing & Compatibility

• License: Not explicitly stated in the README, but a LICENSE.md file is referenced. Users should verify compatibility for commercial use.

Limitations & Caveats

• The specific license type and its implications for commercial use or closed-source linking are not detailed in the README. Users should consult the LICENSE.md file.